SK.FAZARUNNISA BEGUM, Mrs. K. RAJYAM , Y. AMULYA , CH. HARSHA VARDHINI, G. ANUSHA, T. AMULYA 03 02 Brain tumors are a serious health problem and detecting them early is very important for successful treatmentNormally doctors confirm tumors through surgery and biopsy which are invasive methods In this projectartificial intelligence AI is used to provide a noninvasive way of diagnosis By using MRI brain scans deeplearning models are developed to classify gliomas meningiomas pituitary tumors and healthy brain tissuesThe main model used is a Convolutional Neural Network CNN which learns patterns from a large dataset ofMRI images To improve accuracy preprocessing techniques such as normalization scaling and dataaugmentation are applied These steps make the system stronger and reduce false positives and false negativesThe proposed model shows high accuracy in separating tumor and nontumor cases helping doctors make fasterand more reliable decisions This project demonstrates how AI can support medical professionals reducemanual effort and provide precise forecasts Overall it highlights the importance of automated systems inmedical imaging making diagnosis more efficient trustworthy and useful for early detection of brain tumors Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026